Heavy Rainfall Process Research Articles

GPM-based analysis of vertical structure of typical precipitation during 2020 extra-long meiyu season in North Zhejiang

Abstract The Meiyu season during 2020 in China was an extra-long flood season, in particular, the northern region of Zhejiang experienced long duration of precipitation and frequent heavy rainfall processes. In this study, we selected three typical precipitation cases during 2020 ul-tra-long Meiyu season, using dual frequency spaceborne radar data (GPM DPR) revealed the characteristics of precipitation macro-micro vertical structure characteristics at different life cycle. In the development stage, the large-value area of particle diameter (≥2 mm) between 5 km and ground level corresponds to heavy rain zone, while a lower particle number density for the same particle size results in temporarily reduced precipitation efficiency. In the maturity stage, large-scale water condensate particles remain between 5 and 6 km, and cloud anvil structures are identifiable in radar reflectivity factor profiles. In the dissipation stage, with the weakness of the dynamic weather conditions, the height of the radar echo and particle distribution shifts closer to the surface layer. Further analysis of the effect of water condensate particles on surface rainfall intensity shows that the changes from development to maturity and dissipation stages in con-vective precipitation are primarily determined by the hydrometeor particle concentration during the Meiyu season. For stratiform precipitation, it is more closely related to particle concentration parameters. Even when particle concentration and size are high, the absence of strong dynamic mechanisms to trigger latent heat release means raindrops do not continue to grow, resulting in minimal precipitation.

Monitoring Heavy Rainfall Events in East Asia Using High‐Resolution Isotopic Observations

AbstractIt is important to understand the mechanisms of heavy rainfall events, as such information could improve forecasting of these events and help mitigate their adverse impacts on life and property. In this study, we analyzed hourly stable isotopic compositions in water vapor (δ18Ov and d‐excessv) during heavy rainfall events in the summer monsoon season (June to September) from 2013 to 2023 in Nanjing, eastern China. These data were extracted from the longest data set of high‐resolution and continuous in situ observations of water vapor isotopes globally. Based on these data, we identified four evolution patterns of δ18Ov during heavy rainfall events, corresponding to different weather systems: slow‐declining (tropical cyclone interacting with mid‐ and high‐latitude system), W‐shaped (tropical cyclone), U‐shaped (cold vortex system), and inclined L‐shaped (upper‐level trough system). The isotopic variations suggest that heavy rainfall events in eastern China were mainly sustained by moisture from adjacent oceans (including the South China Sea and the East China Sea) and terrestrial environment rather than from the distant Indian Ocean as previously suggested. In addition, for some heavy rainfall events with an intermittent period, the nearby oceanic moisture transport alters before and after the intermittent period due to an intensity change or overall transition of low‐level weather systems. This study serves as a benchmark for tracing heavy rainfall processes in East Asia using high‐resolution water vapor isotopes.

An Evaluation and Improvement of Microphysical Parameterization for a Heavy Rainfall Process during the Meiyu Season

The present study assesses the simulated precipitation and cloud properties using three microphysics schemes (Morrison, Thompson and MY) implemented in the Weather Research and Forecasting model. The precipitation, differential reflectivity (ZDR), specific differential phase (KDP) and mass-weighted mean diameter of raindrops (Dm) are compared with measurements from a heavy rainfall event that occurred on 27 June 2020 during the Integrative Monsoon Frontal Rainfall Experiment (IMFRE). The results indicate that all three microphysics schemes generally capture the characteristics of rainfall, ZDR, KDP and Dm, but tend to overestimate their intensity. To enhance the model performance, adjustments are made based on the MY scheme, which exhibited the best performance. Specifically, the overall coalescence and collision parameter (Ec) is reduced, which effectively decreases Dm and makes it more consistent with observations. Generally, reducing Ec leads to an increase in the simulated content (Qr) and number concentration (Nr) of raindrops across most time steps and altitudes. With a smaller Ec, the impact of microphysical processes on Nr and Qr varies with time and altitude. Generally, the autoconversion of droplets to raindrops primarily contributes to Nr, while the accretion of cloud droplets by raindrops plays a more significant role in increasing Qr. In this study, it is emphasized that even if the precipitation characteristics could be adequately reproduced, accurately simulating microphysical characteristics remains challenging and it still needs adjustments in the most physically based parameterizations to achieve more accurate simulation.

Analysis of Precipitation Zone Forecasts and Examination of Numerical Forecasts for Two Heavy Rainfall Processes in June 2019 in Jiangxi, China 2019

Warm zone rainstorms and frontal rainstorms are two types of rainstorms that often occur in the rainy season in Jiangxi (located in the eastern part of China). The ability to correctly identify the type of rainstorms is important for accurate forecasting of rainstorms. Two heavy rainstorms took place in Jiangxi province. The first heavy rainstorm occurred from 20:00 BJT (Beijing Time) on 6 June to 20:00 BJT on 9 June (referred to as the “6.9” process) and another heavy rainstorm occurred from 20:00 BJT on 21 June to 20:00 BJT on 22 June (referred to as the “6.9” process), 2019. We analyzed the two rainstorms’ processes by using ground-based observation data, NCEP/FNL reanalysis data, ECMWF and CMA-SH9 numerical forecasting products. The results show that: “6.9” process is a warm area rainstorm, and a strong northeast cold vortex exists at 500 hPa geopotential height. The northwesterly flow behind the northeast cold vortex trough is stronger. The position of the northern edge of the subtropical high pressure is more south than that at “6.22” process. The rainstorm is in the precipitation zone of the warm temperature ridge over 925 hPa geopotential height, and with more convective character than “6.22” process. The process of “6.22” is a frontal rainstorm. The convective character of precipitation is weaker. The rainstorm precipitation zones are in a strong temperature front area at 925 hPa geopotential height and there is a tendency for vertical convection to develop into oblique upward convection in the late stage of the rainstorm. The precipitation location and intensity forecast by CMA-SH9 at the “6.9” process is better than that of ECMWF, while ECMWF’s prediction of the precipitation zone and weather condition of the “6.22” process is better.

A Comprehensive Assessment of Multiple High-Resolution Precipitation Grid Products for Monitoring Heavy Rainfall during the “7.20” Extreme Rainstorm Event in China

Precipitation products play an important role in monitoring rainstorm processes. This study takes a rare historical event of extreme, heavy precipitation that occurred in Henan Province, China, in July 2021 as a research case. By analyzing the distribution of the spatial and temporal characteristics of precipitation errors, using a probability density function of the occurrence of precipitation and the daily variation pattern, we assess the capability of a radar precipitation estimation product (RADAR), satellite precipitation products (IMERG and GSMAP), a reanalysis product (ERA5) and a precipitation fusion product (the CMPAS) to monitor an extreme rainstorm in the Henan region. The CMPAS has the best fit with the gauge observations in terms of the precipitation area, precipitation maximum and the evolution of the whole process, with a low spatial variability of errors. However, the CMPAS slightly underestimated the precipitation extremum at the peak moment (06:00–08:00). The RADAR product was prone to a spurious overestimation of the originally small rainfall, especially during peak precipitation times, with deviations concentrated in the core precipitation area. The IMERG, GSMAP and ERA5 products have similar performances, all of which failed to effectively capture heavy precipitation in excess of 60 mm/h, with negative deviations in precipitation at mountainfront locations west of northern Henan Province. There is still a need for terrain-specific error revisions for areas with large topographic relief. By merging and processing precipitation data from multiple sources, the accuracy of the CMPAS is better than any single-source precipitation product. The CMPAS has the characteristic advantage of high spatial and temporal resolutions (0.01° × 0.01°/1 h), which play a positive role in precipitation dynamic monitoring, providing early warnings of heavy rainfall processes and hydrological application research.

Formation Mechanisms of the “5·31” Record-Breaking Extreme Heavy Rainfall Process in South China in 2021

Based on the fifth-generation European Center for Medium-Range Weather Forecasts reanalysis data (ERA5), the real-time observation data from weather stations, and the radar products in Guangdong Province, we analyze the precipitation properties and formation mechanisms of the “5·31” extreme heavy rainfall process with record-breaking 3-h accumulated rainfall in South China during 2021. The results show that the extreme heavy rainfall process is caused by the joint actions of weather systems such as a weak upper-level short-wave trough, a surface stationary front, and a low-level southwesterly jet. Before the heavy precipitation process, there is large precipitable water content and deep warm clouds, which provides a potential for the occurrence and development of the heavy rainfall process in Longhua Town of Longmen County and its surrounding areas. Simultaneously, the low-level southwesterly jet provides abundant warm-wet water vapor for the heavy rainfall area. The vertical atmospheric environmental conditions, such as strong horizontal temperature gradient, high convective available potential energy, high-temperature difference between 850 hPa and 500 hPa, and low convective inhibition, maintain for a long duration in the heavy rainfall area, which are favorable for the occurrence and development of high-efficiency convective precipitation caused by water vapor condensation due to the uplift of low-level warm-wet airflows. The combined effects of the enhanced low-level southwesterly airflow, the stationary front, the mesoscale surface convergence line generated by cold pool outflows, the terrain influence, and the train effect of the precipitation echoes make heavy precipitation near Longhua last longer and stronger than other areas, leading to the extreme heavy rainfall with the record-breaking 3-h accumulated rainfall in Longhua.

Analysis of the Triggering and Maintenance Mechanisms of a Record-Breaking Warm-Sector Extreme-Rainfall Process in Front of an Upper-Level Trough in Tianjin, China

A short-time rainstorm exceeding the extreme historical rainfall occurred in the Jinnan District of Tianjin, China, on 3 July 2022. Due to the concentrated time period of precipitation, it caused serious water accumulation in the Jinnan District. The purpose of this paper is to study the weather mechanism of this extreme rainstorm in the Jinan District of Tianjin. By analyzing the fine observation facts, we can obtain the mesoscale weather characteristics and environmental conditions of the process. The results provide a reference for similar weather forecasting and warning in the future. Based on the 1 min interval precipitation observation data, the ERA5 reanalysis data, the CINRAD-SA radar reflectivity data of Tanggu, the cloud-top brightness temperature data of the Fengyun-4A satellite, and the Variational Doppler Radar Analysis System data, we comprehensively analyzed a record-breaking extreme rainfall process in Tianjin on 3 July 2022. The results show that the extreme rainfall process presents prominent mesoscale weather characteristics, with high precipitation intensity in a short-term period. This process is influenced by multi-scale weather systems, including the 500 hPa upper-level trough and the long-distance water vapor transport by Typhoon Chaba. The rainstorm event is caused by the combined actions of cold pool outflow produced by the upstream precipitation, the easterly disturbance in the boundary layer, the mesoscale temperature front, and the ground convergence line. Specifically, the ground convergence line is formed by the northerly wind of the cold pool outflow and the warm and moist southerly airflow from the ocean, and the temperature front is caused by the horizontal thermal difference of the underlying surface. Both the ground convergence line and temperature front contribute considerably to the triggering of mesoscale convection. The mesoscale secondary circulation is formed in the meridional direction by the meso-γ-scale convergence and its interaction with strong velocity in front of the trough, contributing to the development and maintenance of vertical motion in the Jinnan region of Tianjin and thereby leading to the occurrence and development of this extreme heavy rainfall process.

Localized urban canopy model and improved anthropogenic heat parameters in the weather research and forecasting model: Simulation of a warm-sector heavy rainfall event over the pearl river delta urban agglomeration

Warm-sector heavy rainfall in South China is a frequent type of precipitation in summer in the Pearl River Delta region. The complexity of the mechanisms involved in the triggering of convection, especially the effects of urbanization, has greatly increased the uncertainty of numerical simulations of warm-sector heavy rainfall. In this study, five new surface parameters with five new anthropogenic heat (AH) parameters were constructed and coupled with the urban canopy model (UCM) of the Weather Research and Forecasting model, version 4.1, based on the local climate zone system over the Pearl River Delta Urban Agglomeration (PRDUA). Taking a typical warm-sector heavy rainfall process that occurred in the PRDUA on 20 April 2019 as an example, five groups of experiments involving different schemes were compared and analyzed, revealing that the precipitation simulated using the localized UCM with the new AH parameters was the best (closest to observations). The localized UCM successfully simulated the increase in 2 m temperature and sensible heat flux and the resultant thermal forcing in urban areas, which promoted the convergence of low-level southerly winds with water vapor and the lifting of the lower-layer warm and humid water vapor to the upper layers in the urban center, leading to a significant increase of precipitation. The improved AH parameters enhanced the anthropogenic heat and its vertical conduction in urban areas, but contributed only marginally to the convergence of 10 m winds. Compared with observations from wind profile radar, it was found that the localized UCM enhanced the accuracy of the simulated horizontal wind field convergence at upper and lower levels, while the improved AH parameters enhanced the accuracy of the simulated low-level jet intensity and vertical movement, which are important drivers for the spatial variation in warm-sector heavy rainfall over the PRDUA. The current findings will be helpful for improving the model skill in simulating warm-sector heavy rainfall over high-density urban areas, as well as enhancing understanding of the impact mechanism of urbanization on the occurrence and development of warm-sector heavy rainfall.

Application of Affinity Propagation Clustering Method in Medium and Extended Range Forecasting of Heavy Rainfall Processes in China

Based on the precipitation data of an ensemble forecast from the European Centre for Medium-Range Weather Forecasts, we establish a clustering model named EOF_AP by using the empirical orthogonal function decomposition and the affinity propagation clustering method. Then, using EOF_AP, we conducted research on the identification and classification of the characteristics of medium and extended range forecasts on 11 heavy rainfall events in the middle–lower reaches of the Yangtze River, North China, and the Huanghuai region, from June to September in 2021. We then selected two representative cases to analyze the common characteristics in detail to evaluate the effect of the model. The results show that the EOF_AP clustering model can better identify and classify the main rainfall pattern characteristics, and their corresponding occurrence probability of heavy rainfall processes, on the basis of comprehensively retaining the main forecast information of ensemble members with a few representative types. The rainfall pattern characteristics of some types with low occurrence probability can be identified, such as the extreme type. The distributions of rainfall patterns of the same type are basically consistent, whereas those among different types are distinct. Moreover, through the comparison of the forecast results with different starting times, we analyze the forecast performance of ensemble members and the variation trend of forecast results. We hope this study can provide a reference for the probability forecast of medium and extended range heavy rainfall process.

Influence of the urban canopy on the numerical simulation of the “720” rainstorm process in Beijing

AbstractBased on high‐resolution underlying surface data and revised urban parameters, a heavy rainfall process that occurred on July 20, 2016 in Beijing was simulated using the Weather Research and Forecasting Model, version 4.0 (WRF4.0). Sensitivity experiments by changing the land‐use type and terrain height, and coupling a slab urban canopy model (UCM) with modified parameters, were carried out to investigate the effects of the urban canopy on this rainstorm process in Beijing. The simulation results confirmed that the urban canopy of Beijing had significant impacts on the heavy rainfall, and its impacts on the rainfall could mainly be attributed to the internal structure and related processes of the urban canopy. The urban canopy increased the convergence of water vapor flux in the urban area, leading to strengthened rainfall in the urban area. In addition, employing the UCM also had an influence. The experiment uncoupled with the UCM suggested that the urban heat island effect of Beijing was relatively weak; its barrier effect of the urban canopy played a leading role that blocked and delayed the movement of rain bands, which divided the airflow and increased the amount of rainfall outside the urban area. The experiment coupled with the UCM took into account the parameters of building height, albedo, and anthropogenic heat, which helped improve the accuracy of rainfall simulation. Its urban heat island phenomenon was obvious, which benefited the convergence and upward movement of urban airflow and promoted the movement of the front and the total rainfall in the urban center.

Convection-permitting modeling over the Tibetan Plateau improves the simulation of Meiyu Rainfall during the 2011 Yangtze Plain flood

The Tibetan Plateau (TP) plays a complicated impact on summer extreme precipitation in downstream areas like Yangtze Plain, and the convection-permitting modeling (CPM) over the TP has obvious added value for regional climate simulation. This study investigates whether the CPM over the TP can improve the simulation of a typical extreme Meiyu rainfall in Yangtze Plain and the possible mechanism. To address these issues, we conduct three experiments with the Weather Research and Forecasting (WRF) model using a combination of nesting feedback and different resolution topography. Results reveal that the CPM over the TP better reproduces the regional climate over the TP in terms of the precipitation and temperature. The more realistic representation of the regional climate over the TP can further improve the simulation of the spatial distribution of rainfall, the maximum center of rainfall and heavy rainfall processes of Meiyu rainfall in June 2011 but with a wet bias, which could be attribute to too much convective precipitation caused by the cumulus parameterizations. These improvements mostly benefit from the detailed representation of the complex topography over the TP, which contributes to capturing more reasonable eddy kinetic energy at 500 hPa. Consequently, middle atmospheric cold and downward wind bias over the TP as well as the bias of thermal and mechanical circulation fields (e.g., monsoon flow and South Asia High) are reduced. This work demonstrates the potential for the more realistic representation of atmosphere and land surface information over TP to improve the simulations and prediction of extreme Meiyu rainfall.

A High-precision and Fast Solution Method of Gamma Raindrop Size Distribution based on 0-Moment and 3-Moment in South China

AbstractAccording to the high accuracy linear shape-slope (μ-Λ) relationship observed by several 2-Dimensional-Video-Distrometers (2DVD) in South China, a high-precision and fast solution method of gamma (Γ) raindrop size distribution (RSD) function based on the zeroth order moment (M0) and the third order moment (M3) of RSD has been proposed. The 0-moment (M0) and 3-moment (M3) of RSD can be easily calculated from rain mass mixing ratio (Qr) and total number concentration (Ntr) simulated by the two-moment (2M) microphysical scheme, respectively. Three typical heavy rainfall processes and all RSD samples observed during 2019 in South China were selected to verify the accuracy of the method. Compared to the current widely used exponential RSD with a fixed shape parameter of zero in 2M microphysical scheme, the Γ RSD function using the linear constrained gamma (C-G) method agreed better with the Γ fit RSD from 2DVD observations. The characteristic precipitation parameters (e.g., rain rate, M2, M6 and M9) obtained by the proposed method are generally consistent with the parameters calculated by Γ fit RSD from 2DVD observations. The proposed method has effectively solved the problem that the shape parameter in the 2M microphysical scheme set to a constant, so that the Γ RSD functions are closer to the observations and have obviously smaller errors. This method has a good potential to be applied to the 2M microphysical schemes to improve the simulation of heavy precipitation in South China, but also paves the way for in-depth applications of radar data in numerical weather prediction models.

The Crucial Role of Synoptic Pattern in Determining the Spatial Distribution and Diurnal Cycle of Heavy Rainfall over the South China Coast

AbstractThe South China coast suffers frequent heavy rainfall every warm season. Based on the objective classification method of principal components analysis, the key role of the synoptic pattern in determining the heavy rainfall processes that occurred over the South China coast in the warm season during 2008–18 is examined in this study. We found that heavy rainfall occurs most frequently under three typical synoptic patterns (P1–P3 hereafter) characterized by strong low-level onshore winds. P1 and P3 feature a prevailing southwesterly monsoonal flow in the lower troposphere, with heavy rainfall frequently occurring over the inland windward region in the afternoon associated with the orographic lifting and solar heating. The onshore wind of P3 is stronger than P1 as the western Pacific subtropical high extends more westward to 122°E, which induces stronger low-level convergence along the coastline than P1 when the ageostrophic wind veers from the offshore to onshore direction in the early morning. Hence, a secondary early morning rainfall peak can be found along the coastline. P2 is characterized by a low-level vortex located over the southwest portion of south China. Heavy rainfall under P2 usually initiates over the western part of the coastal region in the morning and then propagates inland in the afternoon. Overall, the synoptic patterns strongly determine the spatial distribution and diurnal cycle of heavy rainfall over the South China coast. This heavy rainfall is closely related to the diurnally varying low-level onshore winds rather than the low-level jets, as well as the different interactions between the low-level onshore winds and the local orography, coastline, and land–sea breeze circulations under different synoptic patterns.

2014年8月18~20日宁波暴雨过程综合分析

2014年8月18~20日宁波暴雨过程综合分析

Wave-activity relation containing wave-basic flow interaction based on decomposition of general potential vorticity* *Project supported by the Strategic Pilot Science and Technology Special Program of the Chinese Academy of Sciences (Grant No. XDA17010105), the National Key Research and Development Project, China (Grant No. 2018YFC1507104), the Key Scientific and Technology Research and Development Program of Jilin Province, China (Grant No. 20180201035SF),

On the basis of the general potential vorticity theorem (GPV), a new wave–activity relation is derived in an ageostrophic and nonhydrostatic dynamic framework. When the Reynolds average is taken, the wave–activity relation shares an exchange term with the equation of the basic-state GPV. Thus, the two equations are capable of presenting the dynamic process of the wave–basic flow interaction. Unlike the E–P flux theory which can only be used in large-scale atmosphere, the corresponding derivation provides a useful tool to analyze the feedback of waves to basic states and the forcing of basic states to waves simultaneously, and it can be used in mesoscale systems, such as heavy rainfall processes. The theory was initially applied to the landfalling Typhoon Mujigae (2015) by assigning the scalar φ to the generalized potential temperature (GPT). The results showed that the newly-derived wave–activity density is able to describe the wave activities associated with strong precipitation in Typhoon Mujigae (2015), including the eyewall and spiral rainbands. However, the interaction between the basic-state vortex and mesoscale waves denoted by the exchange term between basic-state GPV and wave–activity density mainly occurs in the eyewall in Typhoon Mujigae (2015). A comparison of the exchange term with other forcing terms in the newly-derived wave–activity relation indicates that the basic state–wave interaction plays a significant role in enhancing wave activities in the high-precipitation eyewall. By a magnitude analysis of the interaction term, it is found that the strong interaction between basic-state vortex and mesoscale waves is mainly attributed to two factors: the vertical vorticity intensity of the basic-state vortex and the averaged perturbation advection of perturbation GPT which is an exchange between the basic-state GPT and perturbation GPT.

Impact of Urbanization on Heavy Rainfall Events: A Case Study over the Megacity of Bengaluru, India

This study is about the simulation and observational analysis of a heavy rainfall event (HRE) and its sensitivity to land-use changes. The impact of urbanization on processes and mechanisms of rainfall including cloud processes is discussed. This study is based on high-resolution (2 km), time-ensemble simulation of one of the HREs that occurred on 27 May 2017 over the city of Bengaluru in the southern part of India. The simulations are carried out using the Weather Research and Forecasting (WRF) model, which is coupled with a single-layer urban canopy model (UCM). The high-resolution (30 s) land-use data derived from the Indian Space Research Organization (ISRO) for the year 2016–2017 is shown to be realistic in representing the current land-use scenario with a threefold increase in urbanization when compared to USGS land-use data of 1991–1992. Simulation and analysis of large-scale circulation patterns revealed that the event was triggered and sustained by the low-pressure system and cyclonic circulation over the Bay of Bengal. Simulated rainfall was found to be remarkably sensitive to land-use changes as shown by control (USGS) and test (ISRO) simulations. The rainfall intensity and spatial distribution are close to observation in test simulations with relatively less error at station scale with a correlation of 0.49 (95% significance) when compared to control simulations, indicating the importance of realistic representation of land use in the model and its impact on heavy rainfall processes. The test simulation which represents the current urbanization scenario has shown a significant increase in rainfall by over 100–200%. The surface energy fluxes and thermodynamic indices as shown by test simulations are favorable to HREs, and also consistent with the current land-use scenario with increased urbanization. This study demonstrated how a realistic representation of land-use data in the model can help to improve model skill. The main limitation of this research work is that it is based on the generic parameterization of urbanization using single-layer UCM. An in-depth study based on multi-layer UCM and city-specific parameterization of urbanization using sub-kilometer-scale land-use data including buildings would further enhance our understanding on this subject.

How Were the Eastward-Moving Heavy Rainfall Events from the Tibetan Plateau to the Lower Reaches of the Yangtze River Enhanced?

AbstractThis study investigates eastward-moving summer heavy rainfall events in the lower reaches of the Yangtze River (LRYR), which are associated with the Tibetan Plateau (TP) vortices. On the basis of rainfall data from gauges and additional atmospheric data from ERA-Interim, the dynamic and thermodynamic effects of moisture transport and diabatic heating are estimated to determine the physical mechanisms that support the eastward-moving heavy rainfall events. As the rainband moves eastward, it is accompanied by anomalous cyclonic circulation in the upper and middle troposphere and enhanced vertical motion throughout the troposphere. In particular, the rainfall region is located in the fore of the upper-level trough, which is ideal for baroclinic organization of the convective system and further development of the eastward-moving vortex. The large atmospheric apparent heat source (Q1) also contributes for lifting the lower-level air into the upper atmosphere and for enhancing the low-level convective motion and convergence during the heavy rainfall process. Piecewise potential vorticity inversion further verifies the crucial role that the diabatic heating played in developing the anomalous geopotential height favorable for the enhanced rainfall. The combined action of the dynamic and thermodynamic processes, as well as the rich moisture supply from the seas, synergistically sustained and enhanced the eastward-moving rainfall.

Synoptic time-scale variability of sediment temperature profile and sound speed in shallow seas derived from in situ observations

In this study, to investigate the synoptic time-scale variability of sediment temperature profile and sound speed in shallow seas, one-month-long in situ observations were conducted in Jiaozhou Bay using a newly designed sediment measurement system. A typhoon passage and a heavy rainfall process were captured during the observation. The sediment temperature increased immediately after the significant bottom water temperature increase induced by typhoon passage. A significant increase in the sediment warming rate could be identified at a depth as deep as 0.8 m below seafloor (mbs), and a significant increase in downward sediment heat flux at 0.5 mbs lasted until five days after the typhoon passed. The sediment sound speed was also observed to decrease or increase as soon as the bottom water salinity significantly decreased or the bottom water temperature significantly increased. Moreover, the pore water salinity—which can affect the sediment sound speed—cannot be conducted like heat but can be changed only by diffusion or convection processes, and the static diffusion of salt was too slow for the observed sediment sound speed variation; we therefore conclude that in addition to heat conduction, the pore water convection may play an important role in the synoptic time-scale variations of the sediment temperature and sound speed, which is also consistent with the simulation results.

Precise Point Positioning on the Reliable Detection of Tropospheric Model Errors.

Precise point positioning (PPP) is one of the well-known applications of Global Navigation Satellite System (GNSS) and provides precise positioning solutions using accurate satellite orbit and clock products. The tropospheric delay due to the neutral atmosphere for microwave signals is one of the main sources of measurement error in PPP. As one component of this delay, the hydrostatic delay is usually compensated by using an empirical correction model. However, how to eliminate the effects of the wet delay during a weather event is a challenge because current troposphere models are not capable of considering the complex atmosphere around the receiver during situations such as typhoons, storms, heavy rainfall, et cetera. Thus, how positioning results can be improved if the residual wet delays are taken into account needs to be investigated . In this contribution, a real-time procedure of recursive detection, identification and adaptation (DIA) is applied to detect the model errors which have the same effects on both phase and code observables; e.g., the model error caused by the tropospheric delay. Once the model errors are identified, additional parameters are added to the functional model to account for the measurement residuals. This approach is evaluated with Global Positioning System (GPS) data during two rainfall events in Darwin, Australia, proving the usefulness of compensated residual slant wet delay for positioning results. Comparisons with the standard approach show that the precision of the up component is improved significantly during the periods of the weather events; for the two case studies, and improvements of root mean squared error (RMS) resulted, and the precision of the horizontal component obtained by the proposed approach is also improved more than compared to the standard approach. The results also show that the identified model errors are concentrated at the beginning of both heavy rainfall processes when the front causes significant spatial and temporal gradients of the integrated water vapor above the receiver.

浙江一次梅雨期强降水过程的诊断分析

浙江一次梅雨期强降水过程的诊断分析